Mixtral Turbo Instruct on IFEval: score, rank and what it means
Mixtral Turbo Instruct scores 82.1 on IFEval, placing it #275 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.
Score distribution
The chart shows the top 10 models on IFEval, with Mixtral Turbo Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 2 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 3 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 6 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 7 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
| 8 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 9 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 10 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
What this score means
On IFEval, Mixtral Turbo Instruct sits at #275 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 14.0 points. The median model in this index scores 81.2, which puts Mixtral Turbo Instruct above the midpoint.
Together AI models average 74.4 on this benchmark. Mixtral Turbo Instruct is 7.7 points above that provider line, so it is a stronger result than the average Together AI model.
Among open-weight models, the average is 77.0. Mixtral Turbo Instruct is 5.1 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 82.1 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $3.16 per million input tokens, Mixtral Turbo Instruct is below the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Fusion Pro | OpenRouter | 65536 | $8.69 | 72.2 |
| Grok 3 Mini | xAI | 200000 | $9.67 | 73.9 |
| Llama 3 Baseten Chat | Baseten | 200000 | $3.55 | 73.2 |
| Llama 3 Novita Chat | Novita AI | 65536 | $3.50 | 74.2 |
| Mixtral Turbo Instruct | Together AI | 32768 | $3.16 | 71.9 |
| Codestral Chat | Mistral AI | 32768 | $3.89 | 75.8 |
| Command R+ Chat | Cohere | 32768 | $4.02 | 76.0 |
Other benchmarks for Mixtral Turbo Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 72.9 | 369 | 39th | |
| GPQA Diamond | 69.7 | 276 | 54th | |
| SWE-bench Verified | 60.8 | 309 | 49th | |
| HumanEval | 74.2 | 355 | 41th | |
| MATH-500 | 75.9 | 303 | 50th | |
| AIME 2025 | 67.5 | 304 | 49th | |
| LiveCodeBench | 61.4 | 358 | 40th | |
| TruthfulQA | 77.2 | 276 | 54th | |
| HellaSwag | 82.5 | 336 | 44th | |
| MMMU | 66.6 | 365 | 39th | |
| Arena Elo | 1356.6 | 351 | 42th |
FAQ
What score does Mixtral Turbo Instruct get on IFEval?
Mixtral Turbo Instruct scores 82.1 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.
How does Mixtral Turbo Instruct rank on IFEval?
It ranks #275 of 600 models, in the 54th percentile. The leader is Claude Opus 4.5 Pro at 96.1.
Is Mixtral Turbo Instruct good at IFEval?
Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.
How is the IFEval score calculated?
IFEval is a instruction following benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Mixtral Turbo Instruct cost?
Mixtral Turbo Instruct costs $3.16 per million input tokens and $13.04 per million output tokens.